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Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles. (arXiv:2210.10085v1 [cs.IR])
Oct. 20, 2022, 1:11 a.m. | Ivan Srba, Robert Moro, Matus Tomlein, Branislav Pecher, Jakub Simko, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Adrian Gavorni
cs.LG updates on arXiv.org arxiv.org
In this paper, we present results of an auditing study performed over YouTube
aimed at investigating how fast a user can get into a misinformation filter
bubble, but also what it takes to "burst the bubble", i.e., revert the bubble
enclosure. We employ a sock puppet audit methodology, in which pre-programmed
agents (acting as YouTube users) delve into misinformation filter bubbles by
watching misinformation promoting content. Then they try to burst the bubbles
and reach more balanced recommendations by watching …
algorithm arxiv misinformation recommendation recommendation algorithm youtube
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